3-Methylcholanthrene Induces Differential Recruitment of Aryl Hydrocarbon Receptor to Human Promoters
Bibliographic record
Abstract
The aryl hydrocarbon receptor (AHR) is a ligand-activated protein that mediates the toxic actions of polycyclic aromatic and halogenated compounds. Identifying genes directly regulated by AHR is important in understanding the pathways regulated by this receptor. Here we used the techniques of chromatin immunoprecipitation and DNA microarrays (ChIP-chip) to detect AHR-bound genomic regions after 3-methylcholanthrene (3MC) treatment of T-47D human breast cancer cells. We identified 241 AHR-3MC-bound regions, and transcription factor-binding site analysis revealed a strong overrepresentation of the AHR-responsive element. Conventional ChIP confirmed recruitment of AHR to 26 regions with target gene responses to 3MC varying from activation to inhibition to having no effect. A comparison of identified AHR-3MC-bound regions with AHR-2,3,7,8-tetrchlorodibenzo-p-dioxin (TCDD)-bound regions from our previous study (Ahmed, S., Valen, E., Sandelin, A., and Matthews, J. (2009). Toxicol. Sci. 111, 254-266) revealed that 127 regions were common between the data sets. Time course ChIPs for six of the regions showed that 3MC induced gene-specific changes in histone H3 acetylation and methylation and induced differential oscillatory binding of AHR, with a periodicity between 1.5 and 2 h. Re-treatment of cells with 3MC failed to alter the oscillatory binding profiles of AHR or aryl hydrocarbon receptor nuclear translocator. Cells became responsive to 3MC but not TCDD after 24 h of exposure to 3MC, highlighting important differences in AHR responsiveness between the two ligands. Our results reveal a number of novel AHR-bound promoter regions and target genes that exhibit differential kinetic binding profiles and regulation by AHR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".